Abstract—This paper presents a novel self-reconfigurable
robotic system named ACMoD where each module can move
itself individually. It can also attach to other modules to build
various configurations and change this configuration adaptively
on different terrains. In this paper, we have proposed Genetic
Algorithm for optimizing the path of modular robots through a
static grid of different terrain blocks. Each chromosome consists
of path and modular robot configurations. Solution of the
proposed algorithm is a proper path and configuration pattern
for crossing the environment with minimum effort related to a
pre-defined multi-objective function. Finally, for investigating
the efficiency of the proposed algorithm, the performance of
proposed algorithm is compared to Dijkstra algorithm in
different environments.
Index Terms—Dijkstra algorithm, genetic algorithm,
modular robots, path planning.
F. A. Sajad Haghzad Klidbary is with Aritificial Creatures Lab, Electrical
Engineering School, Sharif University of Technology, Tehran, Iran (e-mail:
haghzad@ee.sharif.edu).
S.B. Saeed Bagheri Shouraki is head of Aritificial Creatures Lab,
Electrical Engineering School, Sharif University of Technology, Tehran,
Iran (e-mail: bagheri-s@sharif.edu).
T.C. Salman Faraji is in Ecole Polytechnique Fédérale de Lausanne
(EPFL), Switzerland (e-mail: salman.Faraji@epfl.ch).
Find some videos showing the performance of the robot at
http://ee.sharif.edu/~acl/Projects/ACMoD.
[PDF]
Cite:Sajad Haghzad Klidbary, Saeed Bagheri Shouraki, and Salman Faraji, "Finding Proper Configurations for Modular Robots by Using Genetic Algorithm on Different Terrains," International Journal of Materials, Mechanics and Manufacturing vol. 1, no. 4, pp. 360-365, 2013.
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